Potensi aktivitas antioksidan ekstrak spons laut Stylissa carteri
Bibliographic record
Abstract
Spons laut Stylissa carteri berperan penting karena merupakan salah satu biota penyusun ekosistem pesisir dan laut, terutama pada ekosistem terumbu karang. Spons laut yang makin meningkat pemanfaatan senyawa bioaktifnya, dikhawatirkan dapat mengurangi populasi spons laut secara signifikan. Upaya pencegahannya, yaitu dengan budi daya spons laut untuk pemanfaatan yang berkelanjutan. Penelitian ini bertujuan untuk menentukan aktivitas antioksidan spons Stylissa carteri yang ditransplantasi dan yang hidup alami di alam. Penelitian ini dilakukan di Pulau Pramuka dengan metode kombinasi eksplan spons. Perlakuan transplantasi, yaitu 1: Stylissa carteri (SO), 2: S. carteri dan Aaptos suberitoides (SAP) dan 3: S. carteri, A. suberitoides dan karang keras Acropora (SAC). Pengujian aktivitas antioksidan dengan tiga kali pengulangan pada tiga spons S. carteri hasil transplantasi dan yang hidup alami di alam (SA) menggunakan metode DPPH (1,1-Difenil-2-Pikrilhidrazil). Hasil menunjukkan keempat sumber sampel mengandung aktivitas antioksidan yang kuat, yaitu SO memiliki nilai IC50 86,22±23,6 μg/mL, SAP 86,58±30,7 μg/mL, SAC 86,10±23,4 μg/mL, dan yang hidup alami SA 54,27±16,9 μg/mL. Spons laut jenis S. carteri yang ditransplantasi memiliki kemampuan aktivitas antioksidan yang kuat dan dapat menjadi solusi alternatif dalam aspek ketersediaan bahan baku untuk pengembangan produk farmasi yang potensial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".